Continuous optimisation of outcomes and learning: ensuring long-term impact

In digital transformation, as in life, we crave stability, reliability, purpose, and the feeling that we are doing things today better than we did them yesterday. Small, repeated efforts compound into meaningful change, helping us grow, overcome challenges, and build something that is sustainable for the future.

A consistent, lasting, and ever-improving impact is often missed in government transformation programmes where, despite significant investment, many struggle to deliver change that lasts.¹ This leads to missed opportunities to boost efficiencies and impact, and improve public services at large, through the harnessing of artificial intelligence (AI) and other emerging technologies. 

In the age of enterprise AI, the ability to learn and improve over the long-term takes on a whole new level of significance. We are no longer just talking about continued marginal changes for the better, we are talking about laying data foundations that mean future generations of insight. Our ability to learn at exponential levels is wholly dependent on the quality and consistency of data decisions we make today. 

Delivering and optimising successful outcomes in the public sector is a multi-faceted undertaking. As outlined in earlier articles in this series, transformational change starts with creating clarity of outcomes and is enabled by achieving certainty of outcomes. In this article we explore the final facet of delivering meaningful digital and AI transformation – how can government departments improve long-term impact through continuous optimisation of outcomes and learning? 

1. Adopt a service lifecycle approach

Tangible, consistent technology change is only possible with a corresponding shift in how government approaches service provision. A service lifecycle approach considers how the service will be moved to obsolescence right from its inception. It is designed to ensure that departments make incremental ‘little and often’ improvements to systems while also preparing for the decommissioning of the system at the right time. This reduces the high costs and risks associated with ageing infrastructure while also preparing the way for emerging technology. 

Today we talk about legacy systems as a negative term, meaning systems that hold us back by being out of date. We should be thinking from the outset of any new technical service about “system legacies” – the data foundation that a system will leave behind over its useful life. That legacy can be a source of invaluable insight and a catalyst for continuous improvement. 

To support this approach, it is vital to establish clear accountabilities for moving services through their lifecycle of operation, optimising where possible along the way. For large-scale services, this includes the formation of new roles that ensure that representatives from both business operations and technical service provision are given the right levels of power to ensure systems remain fit for purpose and align with future demand.  

Big or small, all government services should prioritise developing KPIs and long-term metrics with regular reporting and an appreciation of system legacies. This helps keep the focus on driving outcomes-based goals, while allowing for effective monitoring of a potentially complex portfolio of discrete and disparate services. KPIs should be service specific and include comparable metrics, such as drop-off rates, service uptime and reliability, linked to policy outcomes and quantified benefits to measure and highlight the impact of the change.

2. Cultivate a transformation and learning culture  

Successful digital transformation in the public sector is not solely dependent on technology. It requires a fundamental shift in how teams work, collaborate, and continuously improve digital services. 

In an increasingly AI-driven world, it is not just about ability to iterate and learn, it is about ability to plan for data generation and harvesting that supports continuous and compounding learning. Those undertaking this change must evolve from a risk-averse culture to one that encourages experimentation, learns lessons from failure, and iterates based on real-world data and user needs. This is highlighted as a key theme in UK Government’s Data Analytics and AI Project Delivery report, which points to the need to shift public sector behaviours to “experimenting together” in collaboration with “data partnerships”.² Making this shift may not be easy, but it enables the agility, cross-functional collaboration, and rapid decision-making that underpin the successful delivery of digital projects.

It is vital for digital and AI transformation to be seen as a collective endeavour – and not solely the responsibility of departmental digital and data functions. When delivering any major technology initiative, there should be a strong focus on change management and organisational learning. The aim should be to give everyone a stake in change, build their trust in new technologies, and encourage them to experiment and share their learnings. This is crucial for enhancing service delivery and user experiences in the long term across government. 

3. Develop sustainable skills, knowledge management and generational compounding of learning from data

To ensure the continuous optimisation of digital transformation outcomes, government needs to address its digital skills and knowledge retention gap. Only 6% of civil servants are in digital and data roles, while teams across Digital, Data and Technology earn on average 40% less than private sector counterparts.³  This puts an increased burden on the limited in-house digital expertise available, builds a heavy reliance on third parties to augment those capabilities, and therefore drives up overall costs of delivery. 

Government’s approach to attracting and nurturing digital talent must change if it is to maximise the potential of digital and AI initiatives, and continues to stand up its new Government Digital Service (GDS). This does not require matching private sector salaries, but rather highlighting the alternatives to pay (for example flexibility of work and more attractive pension contributions) and the prevalence and impact of its digital outcomes that make public sector work unique. Can government be where ambitious and brilliant people come to do the large, leading-edge solutions that propel UK Plc’s growth? Can large, rich public sector datasets provide opportunities for leading AI solutions? 

Government should consider how to maintain and develop knowledge and skills across the workforce. To achieve this clarity, we recommend prioritising three elements:

• Cross-departmental expertise sharing. Government should develop a platform for sharing digital expertise across government departments that is open and accessible to all and includes information on best practices, case studies, and emerging technology trends. A digital skills exchange programme should be established to enable short-term placements across departments and regular inter-departmental workshops and hackathons should be held to further facilitate knowledge transfer and innovation.
• Digital knowledge retention strategy. A comprehensive knowledge management system should be developed to ensure insight remains available and accessible after individuals or teams depart. Building a knowledge management system involves systematically capturing critical insights, best practice, and technical expertise. This knowledge retention is building towards AI models as the ultimate encapsulation of organisational knowledge in accessible and continually evolving form.
• Digital skills academy. A digital skills academy should be established to train and upskill teams in emerging technologies and digital best practices. By fostering digital literacy and technical proficiency, government can ensure that its workforce can navigate complex projects and leverage emerging technologies to deliver better public services. 

These approaches ensure that public sector digital and AI projects don't just succeed initially, but continue to deliver value over time. Ultimately, this helps government shape enduring digital services that support better use of public resources and meaningful impact for citizens in the years to come.

To learn more about how Baringa can help public sector organisations create lasting impact with digital and AI, please get in touch.

Find out how to build confidence in digital and AI transformation for the public sector

^{1.  The challenges in implementing digital change – National Audit Office}  

^{2.  Data Analytics and AI in Government Project Delivery – GOV.UK}  

^{3.  State of digital government review - GOV.UK}